The Problem
Plant pathogens pose a major threat to agricultural yields all over the world. It is estimated that over 10% of all food production is lost due to pathogens alone1. Pathogens infecting crop plants can cause symptoms spanning from reduced growth up to the death of the host plant234. The responsible pests include bacteria, fungi, oomycetes and viruses56. Different pathogens have to be treated in different ways. But to treat a pathogenic infection the pathogen has to be identified first. This is most commonly achieved by observing the symptoms caused by the pathogen. The problem here is that different pathogens can cause symptoms that are indistinguishable by the naked eye78.
The differentiation is usually done by visually assessing the plants symptoms7. But it requires years of training and experience to become a skilled professional who can do this consistently. And even then, these professionals can’t always tell apart diseases with similar pathologies with 100% certainty. Unfortunately, farmers need this certainty before treating their fields because using as few pesticides as possible is both economically and ecologically important. To achieve the required certainty, samples can be sent to laboratories for analysis via microscopy or PCR. But this is quite expensive and can take up to one month to provide a result. Additionally, this option is only available at later stages of infection, meaning the crops might have already sustained heavy damages and the pathogen had time to spread over bigger parts of the field. Some pathogens only need a few days to complete their life cycle and subsequently infect other plants9. So to maximize crop yields, a faster solution is required!
Our Project
We aim to tackle this problem by designing an easy to use in-field quick test to differentiate between pathogens. The test can detect different pathogens with the help of aptamers. Aptamers are short single stranded nucleic acids that can be used for the same binding applications antibodies are usually used in. We chose to use aptamers as they offer some advantages over antibodies. They are easier to synthesize and offer a high specificity on a wide range of targets10. The aptamer sequences are generated in a process called Systematic Evolution of Ligands by Exponential Enrichment (SELEX). The procedure is based on the random binding of aptamers to the target molecule. After several cycles of incubation, washing and amplification of the aptamers bound to the target, sequences with high binding affinity to the target can be isolated. This binding is caused by the folding of the aptamers into a unique 3D structure that interacts specifically with the target, in our case the pathogens in question. For more information on our SELEX process click here
The test itself is a lateral-flow-assay with an easy colorimetric readout. A sample can be applied to the test and in case the target pathogen is present a red line will appear at the respective position on the test strip, while a second line will always appear as a control. In our project we only focused on the interaction between the model organisms Arabidopsis thaliana and Pseudomonas syringae. But once the SELEX process is established and the test is done it can easily be adapted to other pathogens or crop plants depending on the farmers needs. All that has to be done is to find two aptamer sequences for the new pathogen via SELEX. For more information on our Test development and design process click here
Potential Applications
Due to its adaptability, we suggest this test to be used in three different applications, with only slight alterations to the test needed between them. The first one is to detect plant diseases on seedlings before they are brought out on the field. Some plants, strawberries for example, are not brought onto the field from seeds but rather as young plants bought from plant breeders. This is a huge investment for the farmers, especially for more expensive crops like strawberries or trees. Introducing pathogens this way is a very real threat and can lead to immense financial losses. By testing the plants for common pathogens before they are brought out onto the field the farmers could prevent taking this risk. And that is exactly what our test could offer in an easy and affordable way. It will contain aptamers for all the common pathogens for the respective crop plant. In case of the strawberry those would be Phytophthora cactorum, Colletotrichum gloeosporioides, Macrophomina phaseolina, Xanthomonas fragariae, Botrytis cinerea, Colletotrichum acutatum, Podosphaera aphanis, Phomopsis obscurans and Gnomonia comari11. Sampling would be done either by pooling samples or as spot checks and could be done directly by the farmers without requiring any training or prior knowledge.
For the second application we want to constantly monitor fields with multispectral cameras. With their help we can detect the chlorophyll fluorescence of the plants which correlates with their photosynthetic activity, which in turn is dependent on the plants health1213. Therefore, we can draw direct conclusions to the plants health by observing their chlorophyll fluorescence. In case a plant on the field is infected by a pathogen a drop in chlorophyll fluorescence can be observed way before visible symptoms occur1415. But as we cannot differentiate between pathogens that way, we want to combine this method with our test strip. After detecting a pathogen infection, we will go out into the field and use our test to determine what pathogen is causing the infection, enabling the farmer to act way earlier than otherwise possible. We want to offer this whole application as a subscription service for farmers to solve all their pathogenic worries.
In our third application, the farmer observes symptoms on their plant but cannot determine the pathogenic cause for this because there are multiple pathogens potentially causing these symptoms. In this case our test would only include aptamers for the detection of the specific pathogens in question. Sampling would be done from a piece of infected tissue. It would give a fast and clear result, showing which of the pathogens is causing the disease. This can be followed up by immediate treatment with a suitable pesticide. This application is also suited for direct use by the farmers as it requires no special training or equipment.
Project "Ampelpflanze"
In addition to our test, we also wanted to create a pathogen- and drought-stress reporter for daily lab use and as a model for potential later in field-applications. This is our "Ampelpflanze" as we fondly call it. "Ampelpflanze" translates to "traffic-light plant". It's a transgenic Arabidopsis thaliana plant that changes color depending on the stress it is exposed to. It will turn yellow in case of drought stress and red in case of pathogen stress. The reporter works by fusing a stress-induced promoter to a non-invasive colorimetric reporter gene. So every stressor leads to the induction of a specific promoter which results in its own colorimetric output, making it very clear what kind of stress the plant suffers from. For more information on the design process for "Ampelpflanze" click here
Over the course of our iGEM year we unfortunately were not able to complete a fully functional test, but we are confident that, given a bit more time, this is very achievable. We choose to work with Arabidopsis thaliana and Pseudomonas syringae as they represent a model plant-pathogen interaction. As proof of concept, we designed and built our test with known aptamers for thrombin16 as there are, to our knowledge, no known aptamers for plant pathogens yet. Waiting for our own aptamers was not feasible due to time constraints but we were able to establish our SELEX-protocol, which is already a great achievement.
Overall, we aimed to create a fast solution to the problem of pathogen differentiation. As pathogens and their interactions with plants are very diverse, it had to be easily adaptable. Find out here how our project could affect the world.